code: def render_slicing_metrics(
      result: view_types.EvalResult,
      slicing_column: Optional[str] = None,
      slicing_spec: Optional[
          Union[slicer.SingleSliceSpec, config_pb2.SlicingSpec]
      ] = None,
      weighted_example_column: Optional[str] = None,
      event_handlers: Optional[
          Callable[[Dict[str, Union[str, float]]], None]
      ] = None,
  ) -> Optional[
      visualization.SlicingMetricsViewer
  ]:  # pytype: disable=invalid-annotation
      """Renders the slicing metrics view as widget.
  
      Args:
        result: An tfma.EvalResult.
        slicing_column: The column to slice on.
        slicing_spec: The tfma.SlicingSpec to filter results. If neither column nor
          spec is set, show overall.
        weighted_example_column: Override for the weighted example column. This can
          be used when different weights are applied in different aprts of the model
          (eg: multi-head).
        event_handlers: The event handlers
  
      Returns:
        A SlicingMetricsViewer object if in Jupyter notebook; None if in Colab.
      """
      if slicing_spec and isinstance(
          slicing_spec, config_pb2.SlicingSpec
      ):
          slicing_spec = slicer.SingleSliceSpec(spec=slicing_spec)
      data = util.get_slicing_metrics(
          result.slicing_metrics, slicing_column, slicing_spec
      )
      cfg = util.get_slicing_config(
          result.config, weighted_example_column
      )
  
      return visualization.render_slicing_metrics(
          data, cfg, event_handlers=event_handlers
      )
  
file_path: model-analysis/tensorflow_model_analysis/view/widget_view.py
imports: from typing import Callable, Dict, Optional, Union
  from tensorflow_model_analysis import constants
  import tensorflow_model_analysis.notebook.visualization
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tensorflow_model_analysis.view import util
  from tensorflow_model_analysis.view import view_types
label_desc: Use image node_id 1 for calling a global function with example usage: render_slicing_metrics(result, slicing_column, slicing_spec, weighted_example_column, event_handlers) and returns: visualization